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Andy Chen- By using GWAS (Genome-Wide Association Studies), he found specific genetic markers (pieces of DNA) that are linked to traits that make the wheat more resistant to cold temperatures (winter hardiness). These findings could help improve the ability of winter wheat to survive in colder conditions.

1. What is GWAS?

Scientists use GWAS to scan the entire genotype (DNA) of many individuals to identify which genetic variations are linked to specific phenotypes (traits or diseases). For example, they might look for genetic markers that explain why a plant has a certain height or why a person is more resistant to a disease.

2. What is linkage analysis?

Linkage analysis is a method used to find the location of genes on chromosomes that are responsible for specific traits or diseases. It’s based on the idea that genes that are physically close to each other on a chromosome tend to be inherited together. Linkage analysis helps scientists figure out which genes are passed down from parents to children together, like finding which parts of the DNA "travel" together when traits are inherited. If a certain trait or disease is inherited with a specific gene, it helps narrow down where that gene is located on the chromosome.

3. Difference between GWAS and Linkage analysis?

GWAS:

  • Purpose: Used to find multiple SNPs (single nucleotide polymorphisms) associated with various traits or diseases.
  • Precision: Provides high-resolution mapping, allowing researchers to identify specific genetic variants linked to traits across a large population.
  • Scope: Looks at a wide range of genetic variations and can identify many SNPs, even if they are far apart on the genome.

Linkage Analysis:

  • Purpose: Used to find a particular SNP or gene that is linked to a specific trait or disease within families.
  • Precision: Not as precise as GWAS; it identifies broader regions of DNA rather than pinpointing exact SNPs. It works better for traits that are inherited together in families.
  • Scope: Focuses on the inheritance patterns within families, making it less effective for identifying multiple SNPs across the population.

Summary: GWAS is effective for identifying multiple SNPs associated with various traits and is precise in its mapping. Linkage analysis helps find a specific SNP or gene related to a trait but does so with less precision and often focuses on family data.

4. What is high LD and low LD?

  • Genotype High LD SNP: A "high LD (Linkage Disequilibrium) SNP" means that this genetic variant is strongly linked to nearby variants, so they tend to be inherited together. This happens when the variants are close to each other on the chromosome and there's little recombination between them.
  • Genotype Low LD SNP: A "low LD SNP" is weakly linked to nearby variants, meaning there's more genetic recombination in that region, and they are inherited more independently. In short, high LD = strong link between variants; low LD = weak link 
  • High LD SNP: Suppose there’s a region of the genome where two genetic variants (SNPs) are in high LD. One SNP might be linked to red flower color, and since they are in high LD, another nearby SNP is also usually inherited with this red color trait. So, if a plant has one, it likely has the other.
  • Low LD SNP: In another region, two SNPs are in low LD. One SNP could be linked to taller plant height, but a nearby SNP might not be linked to this trait because they are inherited more independently.
5. Difference between linkage analysis and associative mapping?

Linkage Mapping

  • Focus: Inheritance of traits through controlled breeding.
  • How it Works: It involves crossing specific plants to see how traits are passed to the offspring, identifying genetic markers linked to those traits based on their inheritance patterns.

Association Mapping

  • Focus: Statistical associations in a natural population.
  • How it Works: It examines a large, diverse group of plants without controlled crosses. Researchers look for patterns to see which genetic markers are associated with specific traits, based on existing variation.



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